几种旱地农作物在农田N2O释放中的作用及环境因素的影响

用封闭箱法原位观测几种旱田N₂O的排放通量,并与裸地N₂O通量比较,评价植物在农田N₂O释放中的作用。田间观测与室内模拟实验结合,考察环境因子对N₂O通量的影响。结果表明1d内大豆田N₂O通量有两个释放高峰,而菠菜田和春小麦田只有1个释放高峰。种植大豆较大地提高了农田N₂O的排放通量。农田裸地为一较弱的N₂O释放源,且在1年的一定时期内表现为大气N₂O的汇。光照变化对植物N₂O通量影响很大,在较弱的光照条件下,植物释放N₂O的通量较高。     

控释肥料对稻田氧化亚氮排放的影响

采用静态箱法研究了控释肥料和常规肥料处理对华南赤红壤发育的稻田N₂O排放的影响. 结果表明,施用控释肥处理与非包膜复合肥处理,在水稻移栽后10 d内水层中NH₄+-N和NH₃--N浓度间差异达极显著水平,各处理水层中NH₃--N浓度与2 d后或当天N₂O排放量间的偏相关系数达极显著水平.包膜型控释肥比未包膜复合肥能极显著地降低稻田N₂O的排放量.在施肥后100 d内,控释肥的N₂O累积排放量仅为未包膜型复合肥料的13.45%～21.26%,是尿素处理的71.17%～112.47%.复合肥处理的N₂O排放主要集中在施肥后1～25d和水稻晒田期间,控释肥在此时期的排放量显著降低,尿素处理则延缓并减小了N₂O排放峰.控释肥一次施用和尿素分次施用都能减少N₂O排放.     

控释肥料对覆膜栽培稻田N2O排放的影响

采用静态箱-气相色谱法,研究了控释肥料对四川丘陵地区覆膜节水高产栽培稻田N₂O排放的影响.结果表明: 稻田施用尿素及控释肥料后水稻生长期N₂O排放总量分别为(38.2±4.4)和(21.5±5.2) mg N·m^-2;施用尿素处理N₂O排放系数为0.25%,施用控释肥料处理N₂O排放系数为0.14%,减少了43.6%(P<0.05),其中烤田前减少了49.6%(P<0.05);控释肥料可抑制施肥引起的N₂O排放峰值,降幅达52.6%;控释肥料对水稻不同生长季节土壤微生物生物量氮、NH₄⁺-N含量和水稻产量均无显著影响;N₂O排放与5 cm土壤温度、土壤Eh值无显著相关性.     

氮素配施双氰胺对冬小麦-夏玉米轮作系统N2O排放的影响及效益分析

针对目前集约化农业生产中氮肥用量盲目偏高、氮素利用率低、土壤及肥料中氮素以温室气体N₂O形式的排放量增加等问题,采用田间试验研究了不同氮肥水平(150、225、300 kg·hm^-2)配施双氰胺(DCD)对华北地区集约化农田冬小麦-夏玉米轮作系统N₂O排放的影响,并分析了其经济效益.结果表明： 在整个轮作系统中,不同氮水平配施DCD处理的N₂O排放通量减小25.6%～32.1%,N₂O年度累积排放量降低23.1%～31.1%.土壤N₂O排放通量与表面温度和湿度均呈显著指数相关,且湿度对小麦季N₂O排放的影响大于玉米季,而温度对玉米季的影响大于小麦季.施用DCD后,小麦、玉米产量分别增加16.7%～24.6%和29.8%～34.5%,两季作物经济收益平均增加7973.2 元·hm^-2.因此,合理氮肥用量配施DCD既可以保证作物产量、提高经济效益,又可以减少N₂O排放.综合考虑环境效益与经济效益,本试验条件下中量氮肥配施双氰胺(N总量225 kg·hm^-2)是一种适宜在华北地区推广的优良氮肥管理模式.     

稻麦轮作生态系统中土壤湿度对N2O产生与排放的影响

通过对太湖地区稻麦轮作生态系统的N₂O排放及土壤湿度进行系统观测和开展一系列模拟实验,研究了降雨和土壤湿度对N₂O排放和产生过程的影响.结果表明,春季和秋季麦田N₂O排放与降雨量呈明显正相关,但水稻田和冬季麦田的N₂O排放不受降雨影响.稻麦轮作周期内的N₂O排放较强烈地受土壤湿度制约,土壤湿度为田间持水量的97～100%或84～86%WFPS(土壤体积含水量与总孔隙度的百分比)时,N₂O排放最强,低于此湿度范围时,N₂O排放通量与土壤湿度呈正相关,反之,则呈负相关.田间N₂O排放随土壤湿度的变化形式与模拟条件下培养土壤样品的N₂O产生率变化非常相似,但前者的最佳湿度范围比后者窄,而且偏小.     

高效氮肥对新疆膜下滴灌棉田土壤氧化亚氮排放的影响

高效氮肥对新疆灰漠土农田氧化亚氮(N₂O)排放的影响目前尚不明确.本研究选取树脂包膜尿素(ESN)和尿素配施脲酶抑制剂和硝化抑制剂(U+I)两种高效氮肥处理,以传统尿素(U)处理为对照,研究高效氮肥对新疆膜下滴灌棉田N₂O排放的影响.ESN在播种时一次性施入,而其他处理的氮肥在生育期内随灌溉分次施入.在生育期内,采用静态箱-气相色谱法每周采集和分析2次气体样品.结果表明: 与其他处理相比,ESN处理显著增加了生育期间土壤N₂O的排放量,增幅47%～73%;在施肥后的4个月内,ESN处理下的土壤铵态氮(NH₄⁺-N)和硝态氮(NO₃^--N)含量始终处于较高水平,随后则逐渐减小并与其他处理的含量相近.ESN在播种时全部施入可能是导致土壤高NH₄⁺-N和NO₃^--N含量以及高N₂O排放量的原因.与U处理相比,U+I处理减少了9.9%的N₂O排放量,但两者间差异不显著;U+I处理NO₃^--N含量始终低于ESN和U处理.新疆灰漠土膜下滴灌棉田生育期土壤的N₂O排放为300～500 g N₂O-N·hm^-2,整体低于其他农田生态系统.与播种前全部施入相比,氮肥随滴灌多次施入更利于降低N₂O排放.本试验条件下,高效氮肥对干旱区膜下滴灌棉田土壤N₂O的减排效应有限.     

氮素配施双氰胺对冬小麦-夏玉米轮作系统N2O排放的影响及效益分析

针对目前集约化农业生产中氮肥用量盲目偏高、氮素利用率低、土壤及肥料中氮素以温室气体N₂O形式的排放量增加等问题,采用田间试验研究了不同氮肥水平(150、225、300 kg·hm^-2)配施双氰胺(DCD)对华北地区集约化农田冬小麦-夏玉米轮作系统N₂O排放的影响,并分析了其经济效益.结果表明： 在整个轮作系统中,不同氮水平配施DCD处理的N₂O排放通量减小25.6%～32.1%,N₂O年度累积排放量降低23.1%～31.1%.土壤N₂O排放通量与表面温度和湿度均呈显著指数相关,且湿度对小麦季N₂O排放的影响大于玉米季,而温度对玉米季的影响大于小麦季.施用DCD后,小麦、玉米产量分别增加16.7%～24.6%和29.8%～34.5%,两季作物经济收益平均增加7973.2 元·hm^-2.因此,合理氮肥用量配施DCD既可以保证作物产量、提高经济效益,又可以减少N₂O排放.综合考虑环境效益与经济效益,本试验条件下中量氮肥配施双氰胺(N总量225 kg·hm^-2)是一种适宜在华北地区推广的优良氮肥管理模式.     

氮磷添加对昆仑山北坡高山草地N2O排放的影响

氮(N)、磷(P)等养分添加是提高草地生态系统生产力的重要策略, 但其对土壤氧化亚氮(N₂O)排放的影响尚不明确。该研究以南疆昆仑山北坡高山草地为研究对象, 设置氮添加、磷添加、氮磷交互以及不施肥(CK) 4个处理, 采用静态箱-气象色谱法连续监测2017年生长季草地的N₂O排放, 研究不同氮、磷添加处理下的N₂O排放特征, 并利用Pearson相关分析对影响N₂O排放的主要环境因子进行定性识别及定量解析。结果表明: 氮添加处理与氮磷交互处理在施肥后约3周引起显著的N₂O排放峰, 分别为42.3和15.4 g N·hm ^-2·d ^-1。与其他处理相比, 氮添加处理生长季N₂O排放通量显著增加了1.8-3.2倍, 而磷添加以及氮磷交互处理与CK之间没有显著差异。Pearson相关分析结果表明: N₂O排放与微生物生物量碳呈负相关关系, 与溶解性有机碳含量、pH值呈正相关关系, 而与其他环境因子关系不显著。以上结果表明, 与单施氮肥相比, 在该地区草场采用氮磷混施可显著减少N₂O的排放。     

模拟酸雨对南亚热带典型森林土壤N2O排放的影响

基于长期模拟酸雨森林样地,利用箱式法同步测定了不同酸雨强度处理下森林土壤N₂O排放通量,研究了模拟酸雨对我国南亚热带针阔叶混交林和季风常绿阔叶林两种代表性森林土壤N₂O排放的影响。结果表明: 连续5年(2014—2018年)观测周期内,两种林型土壤N₂O排放通量在各模拟酸雨处理下均表现出明显的季节变化特征,湿季排放通量高于干季,并且年际变化较大。受2017—2018年度降水减少的影响,此期间两种林型土壤N₂O排放通量普遍较低。两种林型土壤N₂O排放通量与土壤温度和土壤湿度呈显著正相关。季风常绿阔叶林对照样方土壤N₂O排放通量为12.6 μg N₂O m^-2·h^-1,与对照相比,pH 3.5和pH 3.0条件下土壤N₂O排放通量分别上升42.9%和61.1%,模拟酸雨显著增加了季风常绿阔叶林土壤N₂O排放通量;模拟酸雨同样有促进针阔叶混交林土壤N₂O排放的趋势,但各处理间差异不显著。在酸雨依旧严峻的形势下,我国南亚热带典型森林土壤N₂O排放通量将增加,且不同林型的增幅不同。     

土壤含水量与N2O产生途径研究

土壤含水量变化对N₂O产生和排放影响的研究表明,不同含水量情况下,N₂O排放也不相同。特别是用乙炔抑制技术证明了在播种前后,气候干燥而土壤含水量较低的情况下,N₂O产生主要来自于硝化过程;降雨后,土壤含水量较高时,N₂O主要是通过反硝化过程产生;而在农田中等含水量情况下,土壤微生物的硝化和反硝化作用产生的N₂O大约各占一半。指出旱作农田N₂O产生途径主要取决于土壤水分的控制和调节。     

基于GIS技术的1991-2000年中国农田化肥氮源一氧化二氮直接排放量估计

依据政府间气候变化专门委员会(IPCC)对农田N₂O排放因子的定义,将气候和种植制度等N₂O排放的主控因素引入到估算方法中,结合GIS技术估计了中国农田化肥氮导致的N₂O直接排放量的空间分布和年际变异.结果表明,在1991—2000年间由于化肥投入量的增加,中国农田化学氮源N₂O排放呈上升趋势.20世纪90年代的平均年排放量为204 Gg N₂O-N,变幅为159～269 Gg N₂O-N,排放量最高的年份出现在1998年,而1992年排放量为最低.估算结果的不确定性约为23％.受施氮量和降水的影响,N₂O排放通量表现出明显的地区差异,东部较高,西北偏低.     

The production and emission of nitrous oxide from headwater streams in the Midwestern United States

The emission of nitrous oxide (N₂O) from streams draining agricultural landscapes is estimated by the Intergovernmental Panel on Climate Change (IPCC) to constitute a globally significant source of this gas to the atmosphere, although there is considerable uncertainty in the magnitude of this source. We measured N₂O emission rates and potential controlling variables in 12 headwater streams draining a predominantly agricultural basin on glacial terrain in southwestern Michigan. The study sites were nearly always supersaturated with N₂O and emission rates ranged from ?8.9 to 266.8 μg N₂O‐N m^?2 h^?1 with an overall mean of 35.2 μg N₂O‐N m^?2 h^?1. Stream water NO₃^? concentrations best‐predicted N₂O emission rates. Although streams and agricultural soils in the basin had similar areal emission rates, emissions from streams were equivalent to 6% of the anthropogenic emissions from soils because of the vastly greater surface area of soils. We found that the default value of the N₂O emission factor for streams and groundwater as defined by the IPCC (EF5‐g) was similar to the value observed in this study lending support to the recent downward revision to EF5‐g. However, the EF5‐g spanned four orders of magnitude across our study sites suggesting that the IPCC's methodology of applying one emission factor to all streams may be inappropriate.     

Estimating annual N2O emissions from agricultural soils in temperate climates

The Kyoto protocol requires countries to provide national inventories for a list of greenhouse gases including N₂O. A standard methodology proposed by the Intergovernmental Panel on Climate Change (IPCC) estimates direct N₂O emissions from soils as a constant fraction (1.25%) of the nitrogen input. This approach is insensitive to environmental variability. A more dynamic approach is needed to establish reliable N₂O emission inventories and to propose efficient mitigation strategies. The objective of this paper is to develop a model that allows the spatial and temporal variation in environmental conditions to be taken into account in national inventories of direct N₂O emissions. Observed annual N₂O emission rates are used to establish statistical relationships between N₂O emissions, seasonal climate and nitrogen‐fertilization rate. Two empirical models, MCROPS and MGRASS, were developed for croplands and grasslands. Validated with an independent data set, MCROPS shows that spring temperature and summer precipitation explain 35% of the variance in annual N₂O emissions from croplands. In MGRASS, nitrogen‐fertilization rate and winter temperature explain 48% of the variance in annual N₂O emissions from grasslands. Using long‐term climate observations (1900–2000), the sensitivity of the models with climate variability is estimated by comparing the year‐to‐year prediction of the model to the precision obtained during the validation process. MCROPS is able to capture interannual variability of N₂O emissions from croplands. However, grassland emissions show very small interannual variations, which are too small to be detectable by MGRASS. MCROPS and MGRASS improve the statistical reliability of direct N₂O emissions compared with the IPCC default methodology. Furthermore, the models can be used to estimate the effects of interannual variation in climate, climate change on direct N₂O emissions from soils at the regional scale.     

Reducing greenhouse gas emissions and adapting agricultural management for climate change in developing countries: providing the basis for action

Agriculture in developing countries has attracted increasing attention in international negotiations within the United Nations Framework Convention on Climate Change for both adaptation to climate change and greenhouse gas mitigation. However, there is limited understanding about potential complementarity between management practices that promote adaptation and mitigation, and limited basis to account for greenhouse gas emission reductions in this sector. The good news is that the global research community could provide the support needed to address these issues through further research linking adaptation and mitigation. In addition, a small shift in strategy by the Intergovernmental Panel on Climate Change (IPCC) and ongoing assistance from agricultural organizations could produce a framework to move the research and development from concept to reality. In turn, significant progress is possible in the near term providing the basis for UNFCCC negotiations to move beyond discussion to action for the agricultural sector in developing countries.     

On the Applicability of Temperature and Precipitation Data from CMIP3 for China

Global Circulation Models (GCMs) contributed to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) and are widely used in global change research. This paper assesses the performance of the AR4 GCMs in simulating precipitation and temperature in China from 1960 to 1999 by comparison with observed data, using system bias (B), root-mean-square error (RMSE), Pearson correlation coefficient (R) and Nash-Sutcliffe model efficiency (E) metrics. Probability density functions (PDFs) are also fitted to the outputs of each model. It is shown that the performance of each GCM varies to different degrees across China. Based on the skill score derived from the four metrics, it is suggested that GCM 15 (ipsl_cm4) and GCM 3 (cccma_cgcm_t63) provide the best representations of temperature and precipitation, respectively, in terms of spatial distribution and trend over 10 years. The results also indicate that users should apply carefully the results of annual precipitation and annual temperature generated by AR4 GCMs in China due to poor performance. At a finer scale, the four metrics are also used to obtain best fit scores for ten river basins covering mainland China. Further research is proposed to improve the simulation accuracy of the AR4 GCMs regarding China.     

Agro-ecological field vulnerability evaluation and climate change impacts in Souma area (Iran), using MicroLEIS DSS

Soil erosion and contamination are two main desertification indices or land degradation agents in agricultural areas. Global climate change consequence is a priority to predict global environmental change impacts on these degradation risks. This agro-ecological approach can be especially useful when formulating soil specific agricultural practices based on the spatial variability of soils and related resources to reverse environmental degradation. Raizal and Pantanal models within the new MicroLEIS framework, the Ero&Con package, are database/expert system evaluation approach for assessing limitations to land use, or vulnerability of the land to specified agricultural degradation risks. This study was performed in Souma area with approximately 4100 ha extension in the North-West of Iran (west Azarbaijan). Based on 35 sampling soils, Typic Xerofluvents, Typic Calcixerepts, Fluventic Haploxerepts and Fluventic Endaquepts were classified as main subgroups. Climatological data, referred to temperature and precipitation of more than 36 consecutive years were collected from Urmieh station reports and stored in monthly Climate Database CDBm, as a major component of MicroLEIS DSS (CDBm) program. Climate data for a hypothetical future scenario were collected from the Intergovernmental Panel on Climate Change (IPCC) reports for the 2080s period. The evaluation approach predicts that attainable water erosion vulnerability classes were none (V1) very low (V2) and moderately low (V4) in the total of 72%, 13% and 15% of the Souma area, respectively and they will not affected by climate change. On contrary, attainable wind erosion vulnerability classes will increase. Also, phosphorous and heavy metal contamination vulnerability risks will not differ in two compared scenarios while nitrogen and pesticides vulnerability classes will be improved.     

两种温室气体排放方案下我国水稻产量变化模拟

利用最新的温室气体和SO₂排放方案,即政府间气候变化委员会(IPCC)排放情景特别报告(SRES)的A2和B2方案,通过区域气候模式PRECIS和作物模型CERES-Rcie相嵌套,在50 km×50 km网格尺度下,模拟了未来2080年我国水稻产量的变化.结果表明,两种温室气体排放方案下,我国水稻的年平均单产水平各地有增有减,增产地区主要集中在长江及长江流域以南地区,其中四川和湖北交界的山区增产幅度最大,减产地区主要集中在华北平原和东北平原;由于CO₂的肥效作用,A2温室气体排放方案对我国水稻单产的正面影响大于B2方案,A2排放方案下,我国水稻总产呈现一定程度的上升趋势,B2排放方案下,水稻总产表现为少量下降.     

The Potential Impact of Agricultural Management and Climate Change on Soil Organic Carbon of the North Central Region of the United States

Soil organic carbon (SOC) represents a significant pool of carbon within the biosphere. Climatic shifts in temperature and precipitation have a major influence on the decomposition and amount of SOC stored within an ecosystem. We have linked net primary production algorithms, which include the impact of enhanced atmospheric CO₂ on plant growth, to the Soil Organic Carbon Resources And Transformations in EcoSystems (SOCRATES) model to develop a SOC map for the North Central Region of the United States between the years 1850 and 2100 in response to agricultural activity and climate conditions generated by the CSIRO Mk2 Global Circulation Model (GCM) and based on the Intergovernmental Panel for Climate Change (IPCC) IS92a emission scenario. We estimate that the current day (1990) stocks of SOC in the top 10 cm of the North Central Region to be 4692 Mt, and 8090 Mt in the top 20 cm of soil. This is 19% lower than the pre-settlement steady state value predicted by the SOCRATES model. By the year 2100, with temperature and precipitation increasing across the North Central Region by an average of 3.9°C and 8.1 cm, respectively, SOCRATES predicts SOC stores of the North Central Region to decline by 11.5 and 2% (in relation to 1990 values) for conventional and conservation tillage scenarios, respectively.     

Estimation of the methane emission factor for the Italian Mediterranean buffalo

In order to contribute to the improvement of the national greenhouse gas emission inventory, this work aimed at estimating a country-specific enteric methane (CH4) emission factor for the Italian Mediterranean buffalo. For this purpose, national agriculture statistics, and information on animal production and farming conditions were analysed, and the emission factor was estimated using the Tier 2 model of the Intergovernmental Panel on Climate Change. Country-specific CH4 emission factors for buffalo cows (630 kg body weight, BW) and other buffalo (313 kg BW) categories were estimated for the period 1990-2004. In 2004, the estimated enteric CH4 emission factor for the buffalo cows was 73 kg/head per year, whereas that for other buffalo categories it was 56 kg/head per year. Research in order to determine specific CH4 conversion rates at the predominant production system is suggested.     

Climate- and crop-responsive emission factors significantly alter estimates of current and future nitrous oxide emissions from fertilizer use

The current Intergovernmental Panel on Climate Change (IPCC) default methodology (tier 1) for calculating nitrous oxide (N₂O) emissions from nitrogen applied to agricultural soils takes no account of either crop type or climatic conditions. As a result, the methodology omits factors that are crucial in determining current emissions, and has no mechanism to assess the potential impact of future climate and land‐use change. Scotland is used as a case study to illustrate the development of a new methodology, which retains the simple structure of the IPCC tier 1 methodology, but incorporates crop‐ and climate‐dependent emission factors (EFs). It also includes a factor to account for the effect of soil compaction because of trampling by grazing animals. These factors are based on recent field studies in Scotland and elsewhere in the UK. Under current conditions, the new methodology produces significantly higher estimates of annual N₂O emissions than the IPCC default methodology, almost entirely because of the increased contribution of grazed pasture. Total emissions from applied fertilizer and N deposited by grazing animals are estimated at 10 662 t N₂O‐N yr^?1 using the newly derived EFs, as opposed to 6 796 t N₂O‐N yr^?1 using the IPCC default EFs. On a spatial basis, emission levels are closer to those calculated using field observations and detailed soil modelling than to estimates made using the IPCC default methodology. This can be illustrated by parts of the western Ayrshire basin, which have previously been calculated to emit 8–9 kg N₂O‐N ha^?1 yr^?1 and are estimated here as 6.25–8.75 kg N₂O‐N ha^?1 yr^?1, while the IPCC default methodology gives a maximum emission level of only 3.75 kg N₂O‐N ha^?1 yr^?1 for the whole area. The new methodology is also applied in conjunction with scenarios for future climate‐ and land‐use patterns, to assess how these emissions may change in the future. The results suggest that by 2080, Scottish N₂O emissions may increase by up to 14%, depending on the climate scenario, if fertilizer and land management practices remain unchanged. Reductions in agricultural land use, however, have the potential to mitigate these increases and, depending on the replacement land use, may even reduce emissions to below current levels.